Tuesday, January 13, 2015

Being in rapidly growing markets (or ones perceived as hot) increases likelihood of success of a company dramatically[1]. Being in a hot market increases the ability to hire great people, get press and awareness, raise money, and eventually exit via M&A or IPO.

The average startup exit takes 7 years. Market hotness increases the likelihood of a fast exit dramatically. In the late 1990's the average time to acquisition or IPO was just 2-3 years due to Internet mania. The fastest exits usually come via M&A. Markets with the most natural acquirers will lead to the most exits in a segment.

To successfully IPO you usually need ~$50 million in revenue and a few quarters of profitability behind you. If you are in a hot market, the profitability constraint may lesson and you can even loose money for a while (see e.g. Hortonworks IPO and big data hotness).

Hot Market Sustainability.

Caveat emptor - about 50% of the markets that are considered hot at any given point turn out to be false alarms. Examples of past hot markets that turned out to largely be duds include First Wave AI (in the 1980s), Nanotech (as an industry in the early 2000s), CleanTech (early to mid 2000s) and Geo (smaller scale in late 2000s).

Hot markets that yielded huge companies and large exits include social networking (mid 2000s -Facebook, Twitter, LinkedIn), and mobile social (early 2010s - WhatsApp, Instagram). Some large market trends are still playing themselves out as per below including big data, sharing economy and other segments.

Hot Markets For 2015

Below is my view of both what markets are hot in 2015, as well as the likelihood of these market segments being medium term duds[2].1. Gold Rush.Markets That Will Yield Large Stand Alone Companies and Many AcquisitionsBig Data.
"Big data" as termed in the press has 4 subsegments[3]:
(1) Dealing with large amounts of data (Hadoop, Spark, etc.)
(2) Smart data. I.e. doing something intelligent with the data you have regardless of the number of petabytes. This is more analytical tools or tools for data scientists.
(3) Data center infrastructure (sometimes this gets clustered into "big data", sometimes not). Mesos (and Mesosphere) would be an example of this.
(4) Verticalized data apps (e.g. data store and analytics for medical insurance claims).

In general this market segment has a lot of legs and will continue to create both stand alone public companies, as well as has a large number of natural acquirers. Potential acquirers include the traditional enterprise companies (HP, IBM, etc.) as well as the earliest companies in the space who support liquid public stock or large market caps (e.g. Cloudera, Hortonworks...). Additionally, the verticalized data companies for healthcare (and 2-3 other key verticals) will see large of exits to more specialized acquirers (e.g. UnitedHealth for healthcare data companies).

SaaS [Software as a Service - including APIs/developer tools]
As recent players with explosive growth (e.g. Zenefits and Slack) have shown, SaaS still has a lot of legs for everything from enterprise collaboration tools to HR back office management.

I would not be surprised if there will be 1-2 very large companies (or exits) created here per year for the next few years. The key will be to find differentiated organic distribution (Slack) or business model (Zenefits).

To prevent the listing of too many submarkets, I will toss APIs/developer tools into this bucket as well. There are lots of services that make sense as an API that traditionally have been performed in a more cumbersome way. Stripe and Twilio are canonical examples of this trend, Checkr.io a more recent one.

Genomics.
Genomics hasn't hit the mainstream hype cycle yet. However I think in late 2015 or early 2016 it will emerge as a hot area of investment due to the fundamental underlying shifts in the market. I think this will yield both a large area of future investment, but also exits ranging in the $100M to multi-billion dollar range. The genomics wave will include both stand alone genomics software companies (lots of natural buyers including IBM, Oracle, Google, Illumina, and others) as well as more traditional biology centric genomics (with large natural buyers in the pharma and traditional biotech markets). I think a small number of large, public companies will emerge in genomics.

2. Silver Mines.Markets That Will Yield Lots of Acquisitions, Less Clear on Independent Stand-AlonesAI.
There are two types of AI companies:
(1) Companies trying to develop general purpose AI or are trying to build a "general AI platform".
(2) Companies applying AI to solve a very specific problem or customer need (e.g. machine translation of web pages or screening pathology samples).

The first group of companies will be small to large acquisitions by Google, Facebook and handful of other companies as talent buys. The second class of companies may yield a small number of large, stand alone, independent businesses. I am more bullish on the prospects of the second group as truly value creating. However, if your primary interest is fast time to exit companies in group (1) will likely sell quickly and at a good valuation 1-4 years post founding as Google and others try to stock up on machine learning talent.

IoT [Internet of Things].
IoT is a sexy rebranding of "consumer electronics and appliances". IoT is modernizing our clunky old school devices in the home and adding software and APIs to allow for seamless interoperability and broaden logging and use of data.

Today's traditional consumer electronics and appliances remind me of the Motorola Razr right before the iPhone - great industrial design but no real use of software.

From an exit perspective large companies like Google, Apple, Samsung, Philips, GE, and others all have an interest in acquiring companies that will accelerate their own efforts in this market. So there are a lot of natural acquirers in the space. I expect more small to large $500M+ exits in this market, but it is unclear to me which of the new batch of companies will create a long term, sustainable public company of their own.

Now that Nest is gone, I would love to hear what others think are the likely long term stand-alone companies in IoT.

Security.
This is a tougher market to crack as a startup hoping to become a massive standalone company, but I expect more startups here in 2015. On the enterprise side there will be ongoing high-profile hackings and the need to purchase security products. Barriers to entry in this market are higher due to the need for both a strong sales channel as well as a differentiated product, which will temper overall market momentum. Basically, a small number of startups will have ongoing small and medium (hundreds of millions of dollars) exits, but the total carrying capacity of this industry is more limited for startups due to sales channel bottlenecks (CIOs will only want to buy security software from a handful of vendors, and too many new startups will focus on a "feature" rather then comprehensive solution).

Recently public Palo Alto Networks and FireEye will likely be industry consolidators as will other traditional enterprise security companies.

3. Roulette.Binary Markets - Create A Few Huge Stand-Alones, Lots of FailuresSharing Economy & On Demand Economy.
Distributed labor and work forces, or the sharing of resources will continue be a hot market from a startup founding perspective. I think the vast majority of the new startups will fail although a handful will still emerge as big hits. Just as Facebook, Twitter, and LinkedIn where the first wave giants in social, AirBnB, Uber, Lyft, Instacart are the first giants of this wave (by market cap).

Similarly, just as there was a second social wave that yielded break out companies (WhatsApp, Pinterest, Instagram) as well as tons of duds, the shared economy/distributed labor trend will have a few more huge companies emerge.

In general this is an area that will be fraught with lots of failures offset by a handful or truly massive outcomes. Too many entrepreneurs will do derivative "Uber for X" for tiny markets ("Uber for sports equipment delivery"). The key will be to figure out how to capture an existing large market (e.g. Uber and transportation) or expand an existing market dramatically (Uber again) with a simple use case and product. The people who win here will win big a they upend entire markets.

4. Tough Short Term Markets For Tech Investors?Bitcoin.
While I am bullish on the long term prospects of crypto currencies and blockchain, I wonder if many of the current crop of companies will succeed. A number of larger structural events need to occur for truly widespread adoption of bitcoin to occur. Existing bitcoin companies have a ticking clock (aka burning through fundraises) relative to this market timing. Profitable (or cash rich) bitcoin companies may make it long enough to see this transition just as AOL did with the Interent[4], but any company burning rapidly through its cash will likely fail. Once a company succeeds sufficiently there will be a large number of potential buyers for BTC companies (including Google, Apple, Microsoft, eBay, and the entire financial system).

I expect there to be an eventual culling of existing bitcoin companies followed in a few years by a massive expansion of cryptocurrency companies when the markets are more mature. This may be a hard slog for a few years punctuated by one or two large, misleading, exits [5]. Then there will be an explosion in cryptocurrency companies that dwarfs the current trend. So, I am extremely bullish on this area long term, but worry about the shorter term dynamics.

Biotech Investments By Software Investors.
Outside of genomics, I have increasingly seen technology investors invest in traditional biotech companies. While genomics has a clear "why now" statement due to its rapidly dropping costs, old school biotech does not share this big shift in market dynamics. In my opinion this market is going to be a fiasco for tech investors as they misunderstand the industry structure (regulatory issues, IP issues etc.) as well as don't have a good sense for the underlying markets. While biotech investors may or may not do well in biotech over the next few years (I honestly don't know the market well enough to be certain) I think a subset tech investors may end up loosing big sums of money here (similar to the CleanTech fiasco of the early 2000s).

Other markets I missed? Comments on existing ones? Let me know on Twitter.

NOTES
[1] "Success" is defined for the purposes of this blog post as the creation of a large stand alone company or a as a large financial exit. This is used as a proxy here for impact to the world, as "impact" is very hard to quantify. How many lives were saved by Google? Yet Google has transformed the world for the better by providing information access to billions of people. It is hard to come up with a good metric for doing good for the world.

[2] Like all prognostication, I will undoubtedly get a bunch of this wrong. This is just my current view of the world, and is obviously subject to change as more data gets generated by that wonderful physics simulation software that we call reality.

[3] From a founder perspective.

[4] AOL is a similar example for the Internet. AOL was founded in the 1980s and managed to work out an existence until the early 90s, when the bigger Internet wave really hit. By the late 90s AOL was one of the largest companies in the world by market capitalization. The next wave of Internet companies were founded a decade later then AOL, when enough infrastructure (markup, browsers, more physical wiring upgrades) allowed for the real Internet boom to occur (Amazon, eBay, Yahoo!, Google, etc.)

Saturday, January 10, 2015

People use the word "platform" to describe products with fundamentally different characteristics. OSs (e.g. Android), infrastructure products (e.g Twilio), and platforms (Facebook APIs e.g. Connect) may all be called "platform". However, the distribution approaches and product strategy for each differs. Conflating what makes a platform work versus e.g. an infrastructure product can backfire and cause a team to have the wrong strategy for building a product or getting customers. These startups tend to fail.

Below I attempt to define and differentiate between these different types of companies and their products.

1. Infrastructure.
Infrastructure products are ones that multiple companies have to build over and over again. Eventually some smart entrepreneur realizes this and builds the common infrastructure product that other companies will pay to use. An example of this is the founders of Mailgun, who built versions of the same email server for multiple employers until they realized they could build this as a general service for all developers.

Infrastructure products are often necessary for a product to function (every ecommerce site needs Stripe for payments) but are not often a "strategic" differentiating buy for their customer (although Stripe has managed to differentiate strategically based on its fast iteration on new features and its simplicity as a product). Early on, many users of Twilio didn't care if they were using Twilio or another telephony provider - they just want it to work quickly, simply, at a good price (which ultimately meant using Twilio due to its ease of use).

The best infrastructure companies have clear economies of scale or network effects. Twilio is probably able to negotiate better and better deals with carriers on pricing the more volume it aggregates from its customers. Similarly, large amounts of payment data can provide scale effects for fraud or risk management.

An infrastructure company's success often boils down to a handful of factors:-Ease of use and integration.-Cost.-Up time.-Differentiated features or historical customer data. This helps you lock in your customer base.-Economies of scale. This can lead to network effects on costs (pricing power of the infrastructure provider relative to its own suppliers) or features (fraud detection).-Developers or sales channel. In some cases a developer ecosystem emerges around an infrastructure product (note: this is different from developers using or adopting a product). This is less common for infrastructure then people think, and is more common for a true "platform" (see below).

In rare cases, an infrastructure company can move up to become a "platform" in its own right. This only works if the infrastructure company is able to collect and re-position unique end user data, or build direct brand recognition with its customer's customers. Platforms typically have more lock-in and differentiation then infrastructure, so moving in this direction if possible can be a strong strategic move.

2. Platform.
A platform almost always grows out of an existing vertical product (e.g. Facebook, Twitter, etc.) and is ultimately a generalized extension of some aspects of that product (e.g. Facebook's internal user graph / identity and Facebook Connect. The resulting platform allows third party developers to take advantage of the unique data, services, or userbase of the original vertical application.

A platform is not easily commoditizable. Only Facebook has the social graph that underlies it, or the ability to drive distribution of certain types of content to a billion users. If a developer tried to use another social product's API (e.g. Foursquare) instead of Facebook's, they would not get access to the right type of data or the same distribution. Alternatively, their own customers would not want to use the "Login with Viddy" button. In contrast, a company could probably swap one infrastructure product for another without a fundamental change to how its own application functions.

Almost always, a platform is valuable due to some unique characteristic of the original vertical product from which it grew. For example, Facebook Connect worked in part because Facebook itself was a representation of a person's identity. It was natural for consumers to feel comfortable logging into other sites with their personal identity. Contrast this to federated approaches like OpenID, to which the user had no brand association. These types of "build it and they will come" approaches to platforms tend to fail (in reality, you are building infrastructure in this case, but calling it a platform, but with no user recognition or branding for your product which comes from being an actual platform).

A platform usually has the following characteristics:-The vertical app the platform is based off of owns the ultimate "end user" directly.
-The core functionality and key features of the platform are derived from the vertical app that spawned it.
-Provides proprietary, non-commodity data and/or distribution to applications using it. The word proprietary here is key.
-In some cases, provides a monetization mechanism for apps on the platform and almost always takes a revenue share. (Contrast this to infrastructure, where the infrastructure provider is paid for use of its product).

Many entrepreneurs I know set out to build a "platform" without any real vertical application underlying it. In reality, they are building infrastructure. Most companies that confuse these two things tend to fail.

The key way to tell if your "platform" product will fail is if you need to build the first "killer app" for the platform yourself for your platform to succeed. In other words, you end up trying to build both a vertical application and a platform simultaneously.

3. Operating System (OS).This is a pretty reasonable definition of an OS. In general, adoption of an OS is driven by the following:-The hardware the OS is typically bundled with gets a lot of distribution.-There exist (or quickly emerge) a small number of killer apps that differentiate the OS causing more distribution and adoption (e.g. spreadsheets and the early PC market).-An app ecosystem emerges around the OS, which creates a positive feedback loop. The more users on an OS, the more people develop apps for it, the more valuable the OS becomes to users.

In general, OSs seem to follow two phases of adoption:
Phase 1: A combination of the hardware plus a small number of killer apps drive OS adoption. For the early PC operating systems this was largely spreadsheet applications like 1-2-3 and Excel.

Phase 2: Once the OS has strong adoption, the longer tail of apps is created by the developer ecosystem who want access to paying users. This locks in users or spreads OS use to a new set of consumers. After the spreadsheet word processing / desktop publishing and gaming helped to spread adoption and value of PCs.

One could argue that a platform is its own killer app first and foremost. For example, the killer app on the Facebook platform is really Facebook. Once Facebook got adoption for itself, other non-Facebook applications followed. This is the primary way a platform product has similarity to an OS.

Who Cares?
The reason these distinctions are important is that the strategy for building a successful Platform is different from building a successful Infrastructure company. Many people confuse the two and pursue the wrong approach as a company.

Signs Your Infrastructure Company Is Off To A Bad Start
Many people call their infrastructure company a "platform" and decide that all they need to do is find a killer app as a customer to drive their own adoption (since the overall market they are gunning for is still hazy and unclear). This type of company is usually started by a non-market driven technologist, who thinks a new technology is really cool. Unfortunately, most of the companies that start off this way end up as small acquisitions at best.

The reason is three-fold:
1. The company is not starting off with a market problem. In the case of a company like Stripe or Twilio, the founders were trying to solve a problem other developers such as themselves faced over and over again.

2. The market may be too small.

3. The "killer app" you are seeking is where all the value in the industry comes from. If the killer app truly took off, it should be able to launch the true platform in the industry and drive you out of business. Unless you are a piece of infrastructure. In which case, where are your customers?